An adaptive large-neighborhood search heuristic for a multi-period vehicle routing problem

被引：58

作者：

Dayarian, Iman ^{[1
]}

Crainic, Teodor Gabriel ^{[2
,4
]}

Gendreau, Michel ^{[3
,4
]}

Rei, Walter ^{[2
,4
]}

机构：

[1] Georgia Inst Technol, Sch Ind & Syst Engn, Atlanta, GA 30332 USA

[2] Univ Quebec, Sch Management, Montreal, PQ, Canada

[3] Ecole Polytech, MAGI, Montreal, PQ, Canada

[4] CIRRELT, CP 8888,Succ Ctr Ville, Montreal, PQ H3C 3P8, Canada

来源：

TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW | 2016年 / 95卷

基金：

加拿大自然科学与工程研究理事会;

关键词：

Multi-period vehicle routing problem with seasonal fluctuations; Tactical planning; Seasonal variation; Adaptive large neighborhood search; CAPACITY EXPANSION; OPTIMIZATION; COLLECTION; ALGORITHM; FRAMEWORK; SOLVE;

D O I：

10.1016/j.tre.2016.09.004

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

This problem involves optimizing product collection and redistribution from production locations to a set of processing plants over a planning horizon. This horizon consists of several days, and the collection-redistribution is performed on a repeating daily basis. A single routing plan must be prepared for the whole horizon, taking into account the seasonal variations in the supply. We model the problem using a sequence of periods, each corresponding to a season. We propose an adaptive large-neighborhood search with several specifically designed operators and features. The results show the excellent performance of the algorithm in terms of solution quality and computational efficiency. (C) 2016 Elsevier Ltd. All rights reserved.

引用

页码：95 / 123

页数：29

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